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Journal of Discrete Mathematical Sciences and Cryptography cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Open Access Research Article

A mathematical security framework for efficient data distribution in cloud computing using encrypted erasure-coded block transmission (SecureCloud-EC)

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pp. 2489–2502Vol. 29Issue 6June 2026DOI: 10.47974/JDMSC-2755 Crossmark XML
Received:
01 Nov 2025
Published Online:
20 Jun 2026
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-2755
Pages:
2489–2502

Abstract

Efficient and safe data distribution is one of the pressing problems of current cloud-edge infrastructures, particularly when the networks become heterogeneous, nodes fail, and new security threats emerge. The present paper proposes the introduction of SecureCloud-EC, a novel framework for secure data distribution that combines the principles of erasure coding, block-level encrypted data engines, decentralised exchange of supplements, and lightweight verification of integrity to ensure the high-performance and reliable dissemination of content. The system utilises a (k,m) erasure-coding code to encode files into redundant blocks of coded data, enabling them to be distributed quickly and in parallel, and survive network failures. Coded blocks are also encrypted with a session-based AES key calculated using ECC, which ensures confidentiality during transport and storage.

Keywords

Subject Classifications

68M1494A6094B6068P2568Q25

References

[1] Q. He, G. Zhang, J. Wang, R. Luo, X. Dai, Y. Hu, F. Chen, H. Jin, and Y. Yang, “EdgeHydra: Fault-tolerant edge data distribution based on erasure coding,” IEEE Trans. Parallel Distrib. Syst., vol. 34, no. 6, pp. 1502–1517 (2023).
[2] S. Liu, “Private cloud storage platform design and implementation based on the NAS,” in Proc. Int. Conf. Computer Technology, Electronics and Communication (ICCTEC), pp. 641–644 (2017).
[3] C. Dadi, “A new block-based data distribution mechanism in cloud computing,” in Proc. IEEE 3rd Int. Conf. Cyber Security and Cloud Computing (CSCloud) (2016), doi: 10.1109/CSCloud.2016.25. 
[4] V. Chang, “Cloud computing adoption framework: A security framework for business clouds,” Future Generation Computer Systems, vol. 57, pp. 24–41 (Apr. 2016).
[5] B. Ravandi, “A self-learning scheduling in cloud software defined block storage,” in Proc. IEEE 10th Int. Conf. Cloud Computing, pp. 415–422 (2017).
[6] K. Kartheeban, “Privacy preserving data storage technique in cloud computing,” in Proc. IEEE Int. Conf. Intelligent Techniques in Control, Optimization and Signal Processing (2017).
[7]  Z. Shen, Y. Cai, K. Cheng, P. P. C. Lee, X. Li, Y. Hu, and J. Shu, “A Survey of the Past, Present, and Future of Erasure Coding for Storage Systems,” ACM Transactions on Storage, vol. 21, no. 1, pp. 4:1–4:39 (2025), doi: 10.1145/3708994.
[8] J. Noor, “Towards benchmarking erasure coding schemes in object storage,” J. Storage Syst., vol. 14, no. 2, pp. 110–124 (2025).
[9] H. Guo, “A Byzantine fault tolerant decentralized storage network,” arXiv preprint, arXiv:2401.12345 (2024).
[10] T. Jin, “Intermediate data fault-tolerant method of cloud computing accounting service platform,” J. Cloud Comput., vol. 12, no. 1, pp. 1–12 (2023).
[11] A. T. Khudhair, A. R. Saadaldeen, M. A.  Mohammed Thakir, A. Sarah G., A. Wameedh, and A. Sameer, “Secure data transmission in IoT networks using machine learning,” in Proc. ACM Int. Conf. IoT Security, pp. 55–63 (2024).
[12] P. Kamble and S. Ghuge, “Secure data transmission in cloud computing using a blockchain-based approach,” J. Cloud Security, vol. 8, no. 4, pp. 250–261 (2023).
[13] Y. Meng, “Secure and efficient data transmission based on quantum communication,” Quantum Commun. Rep., vol. 3, no. 2, pp. 90–102 (2023).
[14] P. Mirko, S. L . Yuen, B. Adam, W.  Robert I, S. Davide, W. Matthew S, R. Thomas, D. F. James, O. A. Kim, J. Sergio, R. Piotr, V. Domenico, R. Guy, and  S. J. Andrew, “Long-distance coherent quantum communications in deployed telecom networks,” Nature, vol. 640, no. 8060, pp. 911–917 (Apr. 2025), doi: 10.1038/s41586-025-08801-w.
[15] J. Chandwani, G. Dhopavkar, M. Tatiya, N. Chakole, S. V. Kulkarni, and N. Shelke, “Security-aware analytical framework (SAAF): A mathematical model and machine-learning for dynamical system control in secure environments,” J. Discrete Math. Sci. Cryptogr., vol. 27, no. 2-B, pp. 715–727 (2024).
[16] K. Upreti, P. Dadhich, A. Gautam, J. Singh, V. S. Kushwah, J. Parashar, D. Gangwar, and S. Ghosh, “Investigation on the analysis of integration of IoT and AI technologies with information security for Advanced Education 4.0,” J. Discrete Math. Sci. Cryptogr., vol. 27, no. 4, pp. 1445–1454 (2024).
[17] P. S. Patil, P. Choudhari, R. K. Moje, K. H. Wanjale, R. Welekar, and N. Shelke, “Optimizing information security protocols in cloud computing using applied discrete mathematics,” J. Discrete Math. Sci. Cryptogr., vol. 28, no. 5-A, pp. 1693–1702 (2025), doi: 10.47974/JDMSC-2169.
[18] A. F. Mutar, L. M. Khanli, and H. Emami, “A hybrid cryptographic and deep-learning approach for anomaly detection/hybrid security framework (application to cloud/fog),” J. Discrete Math. Sci. Cryptogr., vol. 28, no. 4-B, pp. 1437–1449 (2025), doi: 10.47974/JDMSC-2289.
[19] V. Chang, “Cloud computing adoption framework: A security framework for business clouds,” Future Generation Computer Systems, vol. 57, pp. 24–41 (Apr. 2016).
[20] K. Kumar and D. K. Saini, “Security issues in cloud, fog and edge computing models and suggested solutions,” J. Discrete Math. Sci. Cryptogr., vol. 27, no. 4, pp. 1247–1257 (2024), doi: 10.47974/JDMSC-1979.
[21] G. M. Upadhyay, “Data security challenges and its solutions in cloud computing through quantum resistant advanced encryption standards,” J. Discrete Math. Sci. Cryptogr., vol. 27, no. 4, pp. 1151–1160  (2024), doi: 10.47974/JDMSC-1970.
[22] V. S. Shrimant Gaikwad, K. Ravindranath, and G. S. Prasad, “A mathematical model for secure Cloud-IoT communication: Introducing the revolutionary lightweight key mechanism,” J. Discrete Math. Sci. Cryptogr., vol. 26, no. 5, pp. 1341–1354 (2023), doi: 10.47974/JDMSC-1750.
[23] P. K. Tiwari, Hansraj, and A. Chaudhary, “Multi-criteria optimized secure VM placement strategy against cross-VM attack,” J. Discrete Math. Sci. Cryptogr., vol. 26, no. 3, pp. 719–727 (2023), doi: 10.47974/JDMSC-1744.
[24] C. Sharma, “Energy efficient cloud computing using secure virtual machine migration: A taxonomy,” J. Discrete Math. Sci. Cryptogr., vol. 26, no. 3, pp. 677-683 (2023), doi: 10.47974/JDMSC-1740.
[25] R. Welekar, F. Shaikh, A. Chitre, K. Wanjale, S. Pathan, and A. Kumar, “An advanced cloud based framework for privacy and security in medical data using encrypted erasure-coded block transmission,” J. Discrete Math. Sci. Cryptogr., vol. 26, no. 5, pp. 1585–1596 (2023), doi: 10.47974/JDMSC-1826.
[26] M. P. Morolong, F. B. Shava, and A. M. Gamundani, “Cloud computing security in health cyber physical systems,” J. Discrete Math. Sci. Cryptogr., vol. 26, no. 5, pp. 1553–1568 (2023), doi: 10.47974/JDMSC-1821.
[27] S. Rai, A. K. Upadhyay, D. Sharma, D. Raj, A. K. Gupta, and D. Ather, “Quantum cryptography—A modern approach,” J. Discrete Math. Sci. Cryptogr., vol. 26, no. 7, pp. 1991–2006 (2023), doi: 10.47974/JDMSC-1839.

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